A seismic data analysis method and system based on cascaded squeeze time-frequency transform

Abstract

The present invention discloses a seismic data analysis method and system based on cascaded squeeze time-frequency transformation. The optimal large time window is selected according to the minimum Renyi entropy of the short-time Fourier transform under multiple window functions of a single-channel seismic record; according to the selected optimal large time window, the second-order squeeze time-frequency transformation under the optimal large time window is performed; according to the range of the target area of interest, the second-order squeeze time-frequency transformation under the optimal large time window is reconstructed; a series of second-order squeeze time-frequency transformations under smaller time windows are performed according to the reconstructed structure, and the window function corresponding to the minimum reconstruction error is selected as the optimal small time window; the second-order squeeze time-frequency transformation is performed according to the selected optimal small time window, and then the seismic data is analyzed with high precision. The present invention can effectively and accurately extract the time-frequency spectrum of seismic data. By adopting cascaded squeeze time-frequency transformation, it has the characteristics of high resolution, fast speed and accuracy, and can be used for high-precision time-frequency analysis of seismic data.

Description

Technical Field

[0001] The present invention belongs to the technical field of exploration geophysics, and particularly relates to a seismic data analysis method and system based on cascaded squeeze time-frequency transformation. Background Art

[0002] Seismic data analysis can be used not only for reservoir prediction in the field of oil and gas exploration, but also has wide applications in describing the spatial continuity of thin interbeds. Time-frequency analysis, as a powerful tool, is particularly important in seismic data analysis and has been widely applied in actual seismic data analysis. There is still great potential in the future research on the application of time-frequency analysis technology in seismic data analysis. And how to obtain a high-precision time-frequency spectrum of seismic records is the primary prerequisite for subsequent seismic data analysis and processing.

[0003] Currently, the existing time-frequency analysis methods for analyzing seismic data mainly include:

[0004] Prior Art 1: Analyze seismic data through the smoothed pseudo-WVD distribution and Cohen class methods. This technology directly calculates the corresponding time-frequency spectrum of seismic data, and then analyzes the corresponding seismic data attributes according to the characteristics of the time-frequency spectrum. Although this technology is simple to calculate, it is fundamentally difficult to eliminate the cross-term interference in the obtained time-frequency spectrum, resulting in a decrease in time-frequency resolution.

[0005] Prior Art 2: Seismic data analysis technologies represented by squeeze time-frequency analysis. This type of technology mainly rearranges the original time-frequency transformation results in the frequency direction, and can obtain a high-resolution time-frequency spectrum to analyze seismic data. This method has limited time-frequency resolution for multi-frequency component records with close frequencies and fast changes, thus affecting the subsequent seismic data analysis results. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to provide a seismic data analysis method and system based on cascaded squeeze time-frequency transformation for solving the technical problems of cross-term interference and the inability to have both time resolution and frequency resolution existing in traditional methods in view of the above deficiencies in the prior art.

[0007] The present invention adopts the following technical solutions:

[0008] A seismic data analysis method based on cascaded squeeze time-frequency transformation includes the following steps:

[0009] S1. Select the optimal large time window according to the minimum Renyi entropy of the short-time Fourier transform under multiple window functions of a single-channel seismic record;

[0010] S2. Perform a second-order squeeze time-frequency transformation under the optimal large time window selected in step S1;

[0011] S3. Determine the time-frequency range according to the target region of interest, and reconstruct the second-order squeezed time-frequency transform under the optimal large time window obtained in step S2 to obtain a reconstructed signal;

[0012] S4. Perform the second-order squeezed time-frequency transform under a series of smaller time windows on the reconstructed signal obtained in step S3, and select the window function corresponding to the minimum reconstruction error as the optimal small time window;

[0013] S5. Perform the second-order squeezed time-frequency transform according to the optimal small time window selected in step S4, and perform time-frequency analysis on the seismic data.

[0014] Specifically, in step S1, the width σ of the optimal large time window Lopt :

[0015]

[0016] where V(x, g σ ; t, η) is the short-time Fourier transform corresponding to the single-channel seismic data, g σ is the window function, τ is the time variable, and η is the frequency variable.

[0017] Furthermore, the short-time Fourier transform V(x, g σ ; t, η) corresponding to the single-channel seismic data is:

[0018]

[0019] where τ is a temporary variable, x(τ) is the single-channel seismic signal, and i is the imaginary unit.

[0020] Specifically, in step S2, the second-order high-order squeezed time-frequency transform is:

[0021]

[0022] where is the second-order instantaneous frequency at the positions of t and η, δ is the impulse function, ω is the frequency variable, is the optimal large time window.

[0023] Furthermore, the second-order instantaneous frequency at the positions of t and η is:

[0024]

[0025] where represents taking the real part of the complex number, represents that the window function is represents using the window function The result of performing the short-time Fourier transform, is the first-order instantaneous frequency at positions t and η, and q(t, η) is the frequency modulation factor.

[0026] Specifically, in step S3, the reconstructed signal x r (t) is:

[0027]

[0028] where η0 is the lower limit of the reconstruction frequency and η1 is the upper limit of the frequency, is the value of the optimal large time window function at time 0, is the second-order high-order squeezed time-frequency transform.

[0029] Specifically, in step S4, the optimal small time window width σ corresponding to the minimum reconstruction error error(x r , σ) is: Sopt is:

[0030]

[0031] Furthermore, the reconstruction error error(x r , σ) is:

[0032]

[0033] where Δω is an extremely small frequency quantity, x r (t) is the reconstructed signal, and g σ (0) is the value of the window function at time zero, is the second-order squeezed time-frequency transform of the reconstructed signal under the small time window,

[0034] Specifically, in step S5, for the reconstructed signal x r (t) in step S3, the optimal small time window obtained in step S4 is adopted to perform the second-order squeezed time-frequency transform of the reconstructed signal under the optimal small time window using step S2 to finely analyze seismic data from the time-frequency domain.

[0035] In a second aspect, an embodiment of the present invention provides a seismic data analysis system based on a cascaded squeezed time-frequency transform, including:

[0036] A selection module that selects an optimal large time window according to the minimum Renyi entropy of the short-time Fourier transform under multiple window functions of a single-channel seismic record;

[0037] A transformation module that performs a second-order squeezed time-frequency transform under the optimal large time window according to the optimal large time window selected by the selection module;

[0038] A reconstruction module determines a time-frequency range based on a target region of interest, reconstructs the second-order squeezed time-frequency transform under an optimal large time window obtained by a transformation module to obtain a reconstructed signal;

[0039] An optimization module performs second-order squeezed time-frequency transforms under a series of smaller time windows on the reconstructed signal obtained by the reconstruction module, and selects the window function corresponding to the minimum reconstruction error as the optimal small time window;

[0040] An analysis module performs second-order squeezed time-frequency transform according to the optimal small time window selected by the optimization module to perform time-frequency analysis on seismic data.

[0041] Compared with the prior art, the present invention has at least the following beneficial effects:

[0042] A seismic data analysis method based on cascaded squeezed time-frequency transform first performs second-order squeezed time-frequency transform on a single-channel seismic record under a large time window, then reconstructs the target region of interest, and then performs second-order squeezed time-frequency transform on the above reconstruction result under a smaller time window, so that the seismic data can be analyzed according to the second-order squeezed analysis result under the smaller time window. Compared with the existing time-frequency analysis methods of seismic data, the present invention can provide a time-frequency spectrum with extremely high time-frequency resolution, and can be used for seismic processing and interpretation links such as thin layer analysis near the target layer, realizing high-precision time-frequency analysis of seismic data.

[0043] Further, the optimal large time window is selected according to the principle of the minimum Renyi entropy of the short-time Fourier transform time-frequency of the single-channel seismic record under different large time windows, which is beneficial to optimally select the best large time window function among many window functions with different widths.

[0044] Further, calculating the short-time Fourier transform of the single-channel seismic data is beneficial to obtaining the time-frequency spectrum profile of the seismic signal and providing a basic time-frequency transform result for subsequent squeezed time-frequency transform.

[0045] Further, performing second-order squeezing transform on the single-channel seismic record under the optimal large time window is beneficial to obtaining a time-frequency spectrum with high time-frequency resolution and time-frequency characteristics of different frequency bands.

[0046] Further, calculating the second-order instantaneous frequency at the positions of t and η is beneficial to subsequent squeezing operations to squeeze the time-frequency transform coefficients to the correct positions to obtain a high-precision time-frequency transform result.

[0047] Further, reconstructing the target region of the second-order squeezing transform under the large time window is beneficial to extracting specific time-frequency characteristics and reducing the reconstruction error of specific frequency bands.

[0048] Further, selecting the optimal small time window for the reconstruction result based on the principle of minimizing the reconstruction error of the second-order squeezed short-time Fourier transform in different time windows is beneficial to optimally select the best window function from numerous window functions with different widths for the reconstruction result.

[0049] Further, the reconstruction error error(x r ,σ) is the reconstruction error under each small time window, which provides a cost function for subsequent selection of the optimal small time window.

[0050] Further, performing the second-order squeezed time-frequency transform on the reconstruction result under a relatively small time window is beneficial to obtaining a time-frequency spectrum with higher time-frequency resolution. Obtaining seismic attribute information based on the result of the second-order squeezed time-frequency transform under a relatively small time window is beneficial to performing a more refined time-frequency analysis on seismic data.

[0051] It can be understood that the beneficial effects of the second aspect above can be referred to the relevant descriptions in the first aspect above, and will not be elaborated here.

[0052] In summary, the present invention can effectively and accurately achieve the extraction of the time-frequency spectrum of seismic data. By using the cascaded squeezed time-frequency transform, it has the characteristics of high resolution, fast and accurate, and can be used for high-precision time-frequency analysis of seismic data.

[0053] Next, through the drawings and embodiments, the technical solutions of the present invention will be further described in detail. Description of the Drawings

[0054] Figure 1 is the flow chart of the present invention;

[0055] Figure 2 is the illustration of the actual two-dimensional seismic data record and the positions of two wells;

[0056] Figure 3 is the time-frequency spectrum near the target layer of the single-channel data around Well 1 obtained by this method;

[0057] Figure 4 is the time-frequency spectrum near the target layer of the single-channel data around Well 2 obtained by this method. Detailed Embodiments

[0058] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0059] In the description of the present invention, it should be understood that the terms "comprising" and "including" indicate the presence of the described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or their combinations.

[0060] It should also be understood that the terms used in the specification of the present invention are merely for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0061] It should be further understood that the term "and / or" used in the specification of the present invention and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations. For example, A and / or B can represent three cases: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " herein generally indicates that the contextually related objects have an "or" relationship.

[0062] It should be understood that although the terms first, second, third, etc. may be used in the embodiments of the present invention to describe preset ranges, etc., these preset ranges should not be limited to these terms. These terms are only used to distinguish the preset ranges from each other. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0063] Depending on the context, the word "if" as used herein can be interpreted as "when" or "while" or "in response to determining" or "in response to detecting". Similarly, depending on the context, the phrase "if determined" or "if detected (stated condition or event)" can be interpreted as "when determined" or "in response to determining" or "when detected (stated condition or event)" or "in response to detecting (stated condition or event)".

[0064] Various schematic structural diagrams according to the disclosed embodiments of the present invention are shown in the drawings. These figures are not drawn to scale, where for the purpose of clear expression, some details are enlarged and some details may be omitted. The shapes of the various regions and layers shown in the figures and their relative sizes and positional relationships are merely exemplary, and may actually deviate due to manufacturing tolerances or technical limitations, and those skilled in the art can design regions / layers with different shapes, sizes and relative positions according to actual needs.

[0065] The present invention provides a seismic data analysis method based on cascaded squeeze time-frequency transform. According to the time-frequency spectrum characteristics of a single-channel seismic record, an optimal large time window is selected, second-order squeeze time-frequency analysis of the single-channel seismic record is performed under the optimal large time window, and the analysis results of the target area are reconstructed. Finally, an optimal small time window is selected for the above reconstruction results and second-order squeeze time-frequency analysis is performed under the optimal small time window, so as to analyze the seismic data based on the second-order squeeze analysis results under the optimal small time window, realizing high-precision time-frequency analysis of the seismic data.

[0066] Please refer to Figure 1 , a seismic data analysis method based on cascaded squeeze time-frequency transform of the present invention is based on cascaded squeeze time-frequency transform. First, second-order squeeze time-frequency transform of the seismic data is performed under a relatively large time window and reconstruction components are carried out for the area of interest. Secondly, second-order squeeze time-frequency transform of the above reconstruction components is performed under a relatively small time window to finely analyze the seismic data, which is used for seismic processing and interpretation links such as thin layer analysis near the target layer. The specific steps are as follows:

[0067] S1. Calculate the short-time Fourier transform spectra of the seismic trace under different time windows, and select the time window corresponding to the minimum Renyi entropy as the optimal large time window;

[0068] The single-channel seismic data is x(t), and the window function is σ is the window width of the window function.

[0069] Then the short-time Fourier transform corresponding to x(t) is V(x, g σ ; t, η):

[0070]

[0071] where τ is the temporary integration variable and η is the frequency variable.

[0072] Then, the change range of the large time window is given as σ = [σ Lmin … σ Lmax , σ Lmin is the lower limit of the change range of the large time window, and σ Lmax is the upper limit of the change range of the large time window; calculate the short-time Fourier transform results V(x, g σ ; t, η) under different time window parameters, and calculate the Renyi entropy of V(x, g σ ; t, η) under each window function σ:

[0073] Renyi[V(x, g σ ; t, η)] = ∫∫|V(x, g σ ; t, η)| 2 dtdη (2)

[0074] Then select the window width corresponding to the minimum Renyi entropy as the width σ of the optimal large time window. Lopt :

[0075]

[0076] S2. Perform a second-order squeezed time-frequency transform on the selected single-channel seismic record under the optimal large time window;

[0077] The signal is x(t), and the optimal window function is selected as The short-time Fourier transform of x(t) is Then its corresponding second-order high-order squeezed time-frequency transform is

[0078]

[0079] Among them, is the second-order instantaneous frequency at positions t and η, and is obtained through the following method:

[0080]

[0081] Among them, represents taking the real part of the complex number, represents that the window function is represents the result of performing a short-time Fourier transform on the signal x(t) using the window function ;

[0082] The first-order instantaneous frequency at positions t and η is obtained through the following method:

[0083]

[0084] Among them, represents the partial derivative in the t direction;

[0085] The frequency modulation factor q(t, η) is obtained through the following method:

[0086]

[0087] S3. Reconstruct the result obtained from the second-order squeezed time-frequency analysis for a specific frequency band;

[0088] The second-order squeezed time-frequency transform corresponding to the signal x(t) is Then the signal x can be reconstructed for a specific frequency band r (t):

[0089]

[0090] Among them, η0 is the lower limit of the reconstruction frequency, and η1 is the upper limit of the frequency. is the optimal large time window function at the value at time 0.

[0091] S4. Calculate the second-order squeezed Fourier transform of the reconstructed signal under different small time windows, and select the time window corresponding to the minimum reconstruction error of the second-order squeezed Fourier transform as the optimal small time window;

[0092] The change range of the given small time window is σ = [σ Smin … σ Smax , where σ Smin is the lower limit of the time window, and σ Smax is the upper limit of the time window; use the relevant process in step S2 to calculate the second-order squeezed Fourier transform under different small time window parameters Then find the ridge position Ridge(x r , g σ ; t) in the time-frequency spectrum:

[0093]

[0094] Then calculate the second-order squeezed Fourier transform under each small time window along the ridge Ridge(x r , g σ ; t) of the reconstruction error error(x r , σ):

[0095]

[0096] Among them, Δω is a very small frequency quantity (typical value less than 0.1 Hz).

[0097] Finally, select the time window width corresponding to the minimum reconstruction error error(x r , σ) as the width σ of the optimal small time window Sopt :

[0098]

[0099] S5. Perform the second-order squeezed time-frequency transform under the optimal small time window on the reconstruction result, and perform the time-frequency analysis of the seismic data;

[0100] For the reconstructed signal x r (t) in step S3, adopt the optimal small time window obtained in step S4 Use step S2 to obtain the second-order squeezed time-frequency transform of the reconstructed signal under the optimal small time window According to this time-frequency transform in the signal characteristics can be determined accordingly, so as to finely analyze the seismic data from the time-frequency domain.

[0101] In another embodiment of the present invention, a seismic data analysis system based on cascaded squeezing time-frequency transformation is provided. This system can be used to implement the above-mentioned seismic data analysis method based on cascaded squeezing time-frequency transformation. Specifically, the seismic data analysis system based on cascaded squeezing time-frequency transformation includes a selection module, a transformation module, a reconstruction module, an optimization module, and an analysis module.

[0102] Among them, the selection module selects the optimal large time window according to the minimum Renyi entropy of the short-time Fourier transform under multiple window functions of a single-channel seismic record.

[0103] The transformation module performs second-order squeezing time-frequency transformation under the optimal large time window selected by the selection module.

[0104] The reconstruction module determines the time-frequency range according to the target area of interest, and reconstructs the second-order squeezing time-frequency transformation under the optimal large time window obtained by the transformation module to obtain a reconstructed signal.

[0105] The optimization module performs second-order squeezing time-frequency transformation under a series of smaller time windows on the reconstructed signal obtained by the reconstruction module, and selects the window function corresponding to the minimum reconstruction error as the optimal small time window.

[0106] The analysis module performs second-order squeezing time-frequency transformation according to the optimal small time window selected by the optimization module to perform time-frequency analysis on the seismic data.

[0107] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Usually, the components described and shown in the accompanying drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0108] Taking the seismic data of an oilfield with a sampling interval of 1 ms and including 1200-channel records as an example.

[0109] Please refer to Figure 2 , Figure 2 which is a diagram of actual two-dimensional seismic data records and well logging 1 (the position is marked by Well1 in the figure) and well logging 2 (the position is marked by Well2 in the figure). The sampling interval is 1 ms, and there are 1200 seismic records in total.

[0110] Please refer toFigure 3 This is the time-frequency analysis result based on cascaded squeezing time-frequency transform for a seismic data trace (the 75th trace) near Well Log 1.

[0111] From Figure 3 it can be seen that the time-frequency ridge lines of multiple traces have a downward-sloping trend at 1300 ms, indicating that the formation thickness increases with depth. At the same time, the well log curve of Well Log 1 at this location also confirms that the formation thickness gradually increases along the time direction.

[0112] Please refer to Figure 4 This is the time-frequency analysis result based on cascaded squeezing time-frequency transform for a seismic data trace (the 760th trace) near Well Log 2.

[0113] From Figure 4 it can be seen that the time-frequency ridge lines of multiple traces have an upward-sloping trend at 1325 ms, indicating that the formation thickness decreases with depth.

[0114] Correspondingly, the well log curve of Well Log 2 at this location also shows that the layer thickness gradually decreases. Therefore, the time-frequency analysis of the above two target areas verifies the effectiveness of this method in seismic data analysis.

[0115] In summary, for a seismic data analysis method and system based on cascaded squeezing time-frequency transform of the present invention, large-time-window squeezing time-frequency transform is used to obtain a time-frequency transform result with high frequency resolution, and the signal in the time-frequency region of interest is reconstructed based on this. Small-time-window squeezing time-frequency transform is used to obtain a time-frequency transform result with high time resolution. Finally, compared with traditional seismic data time-frequency analysis methods, a time-frequency spectrum with both high frequency resolution and high time resolution can be obtained, which is beneficial for high-precision time-frequency analysis of seismic data.

[0116] Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program code.

[0117] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and combinations of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processors of general-purpose computers, special-purpose computers, embedded processors, or other programmable data processing devices to produce a machine, such that the instructions executed by the processors of the computer or other programmable data processing devices produce means for implementing the functions specified in the Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0118] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory produce a manufactured article including instruction means that implement the functions specified in the Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0119] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in the Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0120] The above is only to illustrate the technical idea of the present invention and should not be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution according to the technical idea proposed by the present invention fall within the protection scope of the claims of the present invention.

Claims

1. A seismic data analysis method based on cascaded squeeze time-frequency transformation, characterized in that It includes the following steps: S1. Select the optimal large time window according to the minimum Renyi entropy of the short-time Fourier transform under multiple window functions of the single-channel seismic record; S2. Perform the second-order squeezed time-frequency transform under the optimal large time window selected in step S1; S3. Determine the time-frequency range according to the target region of interest, and reconstruct the second-order squeezed time-frequency transform under the optimal large time window obtained in step S2 to obtain the reconstructed signal; S4. Perform the second-order squeezed time-frequency transform under a series of smaller time windows on the reconstructed signal obtained in step S3, and select the window function corresponding to the minimum reconstruction error as the optimal small time window; S5. Perform the second-order squeezed time-frequency transform according to the optimal small time window selected in step S4 to perform time-frequency analysis on the seismic data.

2. The seismic data analysis method based on cascaded squeezing time-frequency transform according to claim 1, wherein In step S1, the width σ of the optimal large time window Lopt : Among them, V(x, g σ ; t, η) is the short-time Fourier transform corresponding to single-channel seismic data, g σ is the window function, τ is the time variable, and η is the frequency variable.

3. The seismic data analysis method based on cascaded squeezing time-frequency transform according to claim 2, wherein The short-time Fourier transform V(x, g σ ; t, η) corresponding to the single-channel seismic data is as follows: Where τ is a temporary variable, x(τ) is the single-channel seismic signal, and i is the imaginary unit.

4. The seismic data analysis method based on cascaded squeezing time-frequency transform according to claim 1, wherein In step S2, the second-order high-order squeeze time-frequency transform is as follows: Among them, is the second-order instantaneous frequency at positions t and η, δ is the impulse function, and ω is the frequency variable, is the optimal large time window.

5. The seismic data analysis method based on cascaded squeezing time-frequency transformation according to claim 4, characterized in that The second-order instantaneous frequency at positions \(t\) and \(\eta\) is as follows: Among them, represents taking the real part of a complex number, indicates that the window function is represents applying the window function to the signal x(t) and the result of performing the short-time Fourier transform, is the first-order instantaneous frequency at the positions of t and η, and q(t, η) is the frequency modulation factor.

6. The seismic data analysis method based on cascaded squeezing time-frequency transform according to claim 1, wherein In step S3, the reconstructed signal x r (t) is as follows: where η0 is the lower limit of the reconstruction frequency and η1 is the upper limit of the frequency, is the optimal large time window function at the value at time 0, is the second-order high-order squeezed time-frequency transform.

7. The seismic data analysis method based on cascaded squeeze time-frequency transform according to claim 1, wherein, In step S4, the optimal minimum-hour window width σ corresponding to the minimum reconstruction error error(x r , σ) is Sopt as follows:

8. The seismic data analysis method based on cascaded squeezing time-frequency transformation according to claim 7, wherein The reconstruction error error(x r , σ) is as follows: where Δω is an extremely small frequency quantity, x r (t) is the reconstructed signal, g σ (0) is the value of the window function at time zero, is the second-order squeezed time-frequency transform under the small time window of the reconstructed signal, 9. The seismic data analysis method based on cascaded squeezing time-frequency transformation according to claim 1, characterized in that In step S5, for the reconstructed signal x r (t) in step S3, the optimal small time window obtained in step S4 is used to perform the second-order squeezed time-frequency transform of the reconstructed signal under the optimal small time window obtained in step S2 to finely analyze seismic data in the time-frequency domain.

10. A seismic data analysis system based on cascaded squeeze time-frequency transform, characterized in that, It includes: A selection module that selects the optimal large time window according to the minimum Renyi entropy of the short-time Fourier transform under multiple window functions of the single-channel seismic record; A transformation module that performs the second-order squeezed time-frequency transform under the optimal large time window selected by the selection module; A reconstruction module that determines the time-frequency range according to the target region of interest and reconstructs the second-order squeezed time-frequency transform under the optimal large time window obtained by the transformation module to obtain the reconstructed signal; An optimization module that performs the second-order squeezed time-frequency transform under a series of smaller time windows on the reconstructed signal obtained by the reconstruction module, and selects the window function corresponding to the minimum reconstruction error as the optimal small time window; An analysis module that performs the second-order squeezed time-frequency transform according to the optimal small time window selected by the optimization module to perform time-frequency analysis on the seismic data.

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